About Hassan
- Built and maintained AWS-based ETL infrastructures using Apache Airflow on Linux EC2.
- Designed data lakes with S3 + Athena and integrated RabbitMQ for high-volume streaming.
- Led Databricks/Spark projects for large-scale transformations and analytics.
- Deployed and managed Dockerized ML models in SageMaker for production.
- Tuned SQL Server and Redshift environments for high-traffic analytics.
- Mentored teams and delivered robust solutions under agile frameworks (Jira, ClickUp).
- Data Pipelining & Orchestration (Airflow, Spark, Kafka, Flink, dbt)
- Cloud & Big Data Platforms (AWS, Databricks, Hadoop, Hive)
- Data Streaming (RabbitMQ, real-time processing, concept drift research)
- Database Optimization (SQL Server, PostgreSQL, MySQL, Redshift)
- Automation & Integration (FastAPI, web scraping, APIs)
English
Native or bilingual
German
Basic
Experience
- Marbill TechnologiesSenior Data EngineerAugust 2022 - Today (3 years and 11 months)Marbella, Málaga, Spain• Designed and built a scalable AWS-based ETL infrastructure using Apache Airflow on a Linux EC2 instance.• Integrated RabbitMQ for data streaming, handling sending and receiving data between services and pipelines.• Led a project on Databricks, leveraging its collaborative environment and Spark-based processing for large-scale data transformations and analytics.• Established a test environment mirroring production for development and validation of new pipelines.• Monitored and optimized cloud infrastructure health, performance, and costs, ensuring efficient resource utilization.• Managed and optimized SQL Server database performance to support high-traffic reporting and analytics.• Built a data lake architecture using Athena and S3, serving data scientists, analysts, and data engineers.• Developed, monitored, and optimized several Airflow DAGs to ingest, clean, transform, and process data from various sources (APIs, S3, MySQL Server, RabbitMQ).• Stored processed data in S3, Redshift, and SQL Server, enabling analytics and reporting.• Optimized existing Airflow DAGs and data pipelines for better performance and scalability.• Worked closely with business and marketing teams to translate requirements into data pipelines that support reporting and decision-making.• Assisted the Data Science team by setting up SageMaker instances, training models, and troubleshooting daily issues.• Deployed Dockerized data science models on SageMaker for production use.• Led and mentored a team of 3 data engineers, providing technical guidance and career development support.• Scaled and optimized AWS infrastructure and data pipelines to support business growth and evolving performance needs.• Utilized agile project management platforms such as ClickUp and Jira to coordinate tasks, manage sprints, and ensure timely delivery of data engineering solutions.
- CyshieldData EngineerMay 2021 - July 2022 (1 year and 2 months)Cairo, Cairo Governorate, Egypt• Worked with local servers to support multiple projects, including a search engine, a Netflix-like streaming platform, and an Optical Character Recognition (OCR) system.• Assisted in data modeling for database tables to ensure optimal structure and performance.• Developed web scraping pipelines using Apache Airflow to collect and process data.• Built and deployed REST APIs using FastAPI to support application functionality and data access.• Integrated Grafana for real-time monitoring and visualization of system performance and data pipelines.• Managed and optimized the deployment of data pipelines, APIs, and databases (PostgreSQL) to ensure smooth operation.
- Nile UniversityData Engineer | Data Streaming ResearchAssistantOctober 2020 - October 2022 (2 years)Giza, El Omraniya, Giza Governorate, Egypt• Spearheaded research on online machine learning and concept drift detection, evaluating and adapting drift detection methods for improved performance across diverse data stream scenarios.• Developed and implemented an adaptive bucket dropping technique that significantly reduced memory consumption while maintaining drift detection accuracy.• Designed and executed extensive experiments on both synthetic and real-world datasets to assess throughput, drift detection performance, and resource utilization.• Main Author of the ACM conference paper, (DOI: 10.1145/3477314.3507074), addressing efficiency improvements in data stream analytics.• Contributed as a co-author to a Springer publication (DOI: 10.1007/978-3-031-21595-7_4), advancing the understanding of concept drift adaptation techniques in online machine learning.• Collaborated with interdisciplinary research teams, sharing insights and validating experimental methodologies to drive innovation in streaming analytics.• Presented findings at academic conferences, contributing to the broader research community and influencing future studies in data stream processing.• Served as a member of the judges committee for university research papers and undergraduate projects, evaluating academic work and fostering research innovation.
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Education
- master's degreeNile Universitymaster's degree
- Master of InformaticsNile University2023Master of Informatics